MARATTO

article · International Journal of Biomedical Imaging

Qualitative and Quantitative Evaluation of the Image Quality of MDCT Multiphasic Liver Scans in HCC Patients

20251 citationOpen accessSuez University

Abstract

Background: The quality of CT images obtained from hepatocellular carcinoma (HCC) patients is complex, affecting diagnostic accuracy, precision, and radiation dose assessment due to increased exposure risks. Objectives: The study evaluated image quality qualitatively and quantitatively by comparing quality levels with an effective radiation dose to ensure acceptable quality accuracy. Materials and Methods: This study retrospectively reviewed 100 known HCC patients (Li‐RADS‐5) who underwent multidetector computed tomography (MDCT) multiphasic scans for follow‐up of their health condition between January and October 2023. The evaluation involved quantitative and qualitative analyses of parameters such as SD, SNR, and CNR, as well as a qualitative assessment by two radiology consultants. The outcomes were compared, and the effective dose was calculated and compared with both quantitative and qualitative assessments of image quality. Results: ROC curve analysis revealed significant differences in CT image quality, with high to moderate specificity and sensitivity across all the quantitative parameters. However, multivariate examination revealed decreasing importance levels, except for CNR ( B , 0.203; p = 0.001) and SD BG ( B , 0.330; p = 0.002), which increased in B . The CNR and SD BG remained independent variables for CT image quality prediction, but no statistically significant relationship was found between the effective dose and image quality, either quantitatively or qualitatively. Conclusion: This study underscores the vital role of both quantitative and qualitative assessments of CT images in evaluating their quality for patients with HCC and highlights the predictive importance of CNR, SNR, and SD. These findings emphasize the value of these devices in assessing and predicting outcomes to minimize the effective dose.

Research topics

  • Radiation Dose and Imaging
  • Advanced X-ray and CT Imaging
  • Radiomics and Machine Learning in Medical Imaging

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1155/ijbi/4163865

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.